No abstract

Background: Lung cancer causes approximately 25% of all cancer deaths. Despite its relevance, few studies have analyzed differences by sex at the time of diagnosis in terms of symptoms, stage, age or smoking status.We aim to assess if there are differences between men and women on these characteristics at diagnosis. Methods:We analyzed the Thoracic Tumour Registry (TTR), sponsored by the Spanish Lung Cancer Group using a case-series design. This is a nationwide registry of lung cancer cases which started recruitment in 2016. For each case included, clinicians fulfilled an electronic record registering demographic data, symptoms, exposure to lung cancer risk factors, and treatment received in detail. We compared men and women using descriptive statistics.Results: A total of 13,590 participants took part in this study, 25.6% women. Women were 4 years younger than men (64 vs. 69), and men had smoked more frequently. Adenocarcinoma was the most frequent histological type in both sexes. Stage IV at diagnosis was 50.8% in women compared to 43.6% in men.Weight loss/anorexia/asthenia was the most frequent symptom in both sexes and there were no differences in the number of symptoms at diagnosis. There were no relevant differences in the frequency or number of symptoms by sex when non-small cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) were analyzed separately. Smoking status did not appear to cause different lung cancer presentation in men compared to women. 2 Ruano-Ravina et al. Sex differences at lung cancer diagnosis

No abstract

Plasma samples from 72 EGFR‐mutant advanced NSCLC patients, collected upon progression to first‐line TKI, were analyzed by seven methodologies (two NGS‐based methods, three high‐sensitivity PCR‐based platforms, and two FDA‐approved methods). Our study demonstrates a good to excellent agreement between methodologies and supports the use of liquid biopsies for therapy decision‐making.

Background There is a lack of useful diagnostic tools to identify EGFR mutated NSCLC patients with long-term survival. This study develops a prognostic model using real world data to assist clinicians to predict survival beyond 24 months. Methods EGFR mutated stage IIIB and IV NSCLC patients diagnosed between January 2009 and December 2017 included in the Spanish Lung Cancer Group (SLCG) thoracic tumor registry. Long-term survival was defined as being alive 24 months after diagnosis. A multivariable prognostic model was carried out using binary logistic regression and internal validation through bootstrapping. A nomogram was developed to facilitate the interpretation and applicability of the model. Results 505 of the 961 EGFR mutated patients identified in the registry were included, with a median survival of 27.73 months. Factors associated with overall survival longer than 24 months were: being a woman (OR 1.78); absence of the exon 20 insertion mutation (OR 2.77); functional status (ECOG 0–1) (OR 4.92); absence of central nervous system metastases (OR 2.22), absence of liver metastases (OR 1.90) or adrenal involvement (OR 2.35) and low number of metastatic sites (OR 1.22). The model had a good internal validation with a calibration slope equal to 0.781 and discrimination (optimism corrected C-index 0.680). Conclusions Survival greater than 24 months can be predicted from six pre-treatment clinicopathological variables. The model has a good discrimination ability. We hypothesized that this model could help the selection of the best treatment sequence in EGFR mutation NSCLC patients.